Hands-On Machine Learning Training

The Hands-On Machine Learning Training works through supervised and unsupervised learning, deep learning and NLP applications in Python. The program starts with setting up the Python environment, the core libraries NumPy, Pandas, Matplotlib and Seaborn, exploratory data analysis and data cleaning and preprocessing. Linear and logistic regression, decision trees, Random Forest, Gradient Boosting, KNN, SVM, clustering and PCA are covered next. The deep learning section covers neural network fundamentals, CNNs for image classification and RNNs for time series and text data. NLP work covers text preprocessing, Bag-of-Words, TF-IDF and sentiment analysis. The course continues with hyperparameter tuning via Grid Search and Random Search and concludes with a mini project on a real dataset.